Inverted EEMD: a robust method to identify narrow absorption features form spectral data and cubes

TL;DR

The paper introduces an inverted EEMD method that automatically and robustly extracts narrow absorption features from spectral data cubes, aiding the analysis of complex astrophysical signals like HI self-absorption clouds.

Contribution

It presents a novel, parameter-free, and robust method based on EEMD to identify narrow absorption features in spectral cubes, improving analysis of complex astrophysical data.

Findings

Successfully extracts narrow absorption features from spectral cubes

Produces separate absorption and unabsorbed signal maps

Applicable to various types of localized absorption signals

Abstract

Extracting information from complex data is a challenge shared by multiple frontiers of modern astrophysical research. Among those, analyzing spectra cubes, where the emission is mapped in the position-position-velocity space is a difficult task given the vast amount of information contained within. The cubes often contain a superposition of emissions and absorptions, where extracting absorption signatures is often necessary. One example is the extraction of narrow absorption structures in HI 21 cm emission spectra. These HI self-absorption (HISA) clouds trace the cold HI gas in interstellar space. We introduce an automatic and robust method called the \emph{inverted EEMD} method to extract narrow features from spectral cubes. Our method is based on the EEMD method, an established method to decompose 1d signals. The method is robust and parameter-free, making it useful in analyzing spectral cubes containing localized absorption signals of different types. The inverted-EEMD method is suitable for the analysis of spectral cubes where it can produce a cube containing the absorption signal and one containing the unabsorbed signal, where cold clouds can be identified as coherent regions in the absorption map. A Python implementation of the method is available at \url{https://github.com/zhenzhen-research/inverted_eemd_map}.